This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The influenza membrane glycoproteins, particularly neuraminidase, which is a major antiviral target, are remarkably flexible proteins. Thus it is highly likely that development of new antivirals will depend on our ability to account for and design around this flexibility. This presents a key methodological challenge to the drug discovery community and is one that we are actively pursuing. The overall goals of this collaborative project are to utilize our new computational tool to optimize compounds discovered in virtual screens and then obtain key experimental data in order to improve the current docking approaches for large and highly flexible ligands and receptors. The Wilson lab (TSRI) is a pioneer in determining structures of influenza proteins and is presently testing our first set of newly discovered compounds, which were discovered using the recently developed relaxed complex scheme (RCS) ensemble-based virtual screening technique (presented in (Cheng et al., 2008)), in neuraminidase inhibition assays. Crystallographic data on the precise binding modes of the most promising compounds will also be obtained. These compounds and their binding modes will subsequently be used in the refinement of the project computer-aided drug design (CADD) technique. Based on these results, the McCammon lab will then optimize the compounds using a new AutoDock-based approach to compound optimization that again takes receptor flexibility into account. After optimization, our synthetic collaborators in the Sharpless lab (TSRI) will synthesize the most promising compounds we predict and the Wilson lab will determine their binding modes. Multiple rounds of optimization are envisioned, with the ultimate goal being the development of new compounds that take advantage of the flexibility in the N1 active site region, as compared to other subtypes. The experimental data that we generate will play a critical role in the verification and refinement of the theoretical approach and will aid in the development of new lead compounds that could be developed into antiviral drugs.